Visualize customer appointment trends

A retail brand in NYC wanted to unlock insights from their customer appointment data.

I built a data pipeline from their appointment software by writing a serverless function in Python on Google Cloud to call the REST API daily. The Python script transformed the JSON from the API into a format suitable for a SQL database. I loaded the data into the BigQuery data warehouse. I then created an intuitive dashboard on Looker Studio for the CX team.

I created one graph showing cancellation and no-show rates. The CX team was able to see easily that sending a confirmation SMS reduced no-show rates.

Another chart compared the ratio of walk-in customers vs appointments made online. The data showed that 2nd floor retail stores had significantly fewer walk-in customers. This insight impacted the company's real estate strategy.